install.packages("tidyverse")
reg<-matrix(c(17,3.4,194,38.8,48,9.6,3,0.6,238,47.6), ncol=2, byrow = TRUE)
rownames(reg) <-c("Asian/Pasific Islander","Black","Native American","Unknown","White")
colnames(reg) <-c("Male","Female")
reg=as.table(reg)
reg
reg<-matrix(c(17,3.4,194,38.8,48,9.6,3,0.6,238,47.6), ncol=2, byrow = TRUE)
rownames(reg) <-c("Asian/Pasific Islander","Black","Native American","Unknown","White")
colnames(reg) <-c("Homicide Case","Murder rate (2010-2014")
reg=as.table(reg)
reg
reg<-matrix(c(17,3.4,194,38.8,48,9.6,3,0.6,238,47.6), ncol=2, byrow = TRUE)
rownames(reg) <-c("Asian/Pasific Islander","Black","Native American","Unknown","White")
colnames(reg) <-c("Homicide Case","Murder rate (2010-2014)")
reg=as.table(reg)
reg
reg<-matrix(c(17,3.4,194,38.8,48,9.6,3,0.6,238,47.6), ncol=2, byrow = TRUE)
rownames(reg) <-c("Asian/Pasific Islander","Black","Native American","Unknown","White")
colnames(reg) <-c("Homicide Case","Murder rate (2010-2014)")
reg=as.table(reg)
reg
#table data
reg<-matrix(c(17,3.4,194,38.8,48,9.6,3,0.6,238,47.6), ncol=2, byrow = TRUE)
rownames(reg) <-c("Asian/Pasific Islander","Black","Native American","Unknown","White")
colnames(reg) <-c("Homicide Case","Murder rate (2010-2014)")
reg=as.table(reg)
reg
x<-c(17,194,48,3,238)
y<-c(3.4,38.8,9.6,0.6,47.6)
#scatter plot
plot(x,y)
cor (x,y)
mod<-lm(y)
summary(mod)
attributes(mod)
mod$coef
coef(mod)
plot(x,y, xlab="Homicide Case", ylab = "Murder Rate", col="coral2", main = "Regression")
abline(mod, col=1,lwd=1)
confint(mod)
library(A3)
library(askpass)
library(assertthat)
library(backports)
library(base64enc)
library(BH)
library(blob)
library(broom)
library(callr)
library(classInt)
library(cellranger)
library(clipr)
library(cli)
library(colorspace)
library(crayon)
library(curl)
library(DBI)
library(dbplyr)
library(desc)
library(digest)
library(dplyr)
library(e1071)
library(ellipsis)
library(evaluate)
library(fansi)
library(farver)
library(forcats)
library(fs)
library(generics)
library(ggplot2)
library(glue)
library(gtable)
library(haven)
library(highr)
library(hms)
library(htmltools)
library(isoband)
library(httr)
library(jpeg)
library(jsonlite)
library(knitr)
library(labeling)
library(lifecycle)
library(lmtest)
library(magrittr)
library(markdown)
library(mime)
library(modelr)
library(openssl)
library(munsell)
library(pillar)
library(pkgbuild)
library(pkgconfig)
library(pkgload)
library(plotrix)
library(plyr)
library(png)
library(praise)
library(prettyunits)
library(processx)
library(progress)
library(ps)
library(purrr)
library(R6)
library(raster)
library(RColorBrewer)
library(Rcpp)
library(readr)
library(readxl)
library(rematch)
library(reprex)
library(reshape2)
library(rgdal)
library(rlang)
library(rprojroot)
library(rstudioapi)
library(rmarkdown)
library(rvest)
library(scales)
library(selectr)
library(stringi)
library(stringr)
library(sys)
library(tibble)
library(testthat)
library(tidyr)
library(tidyselect)
library(tidyverse)
library(tinytex)
library(utf8)
library(vcd)
library(vctrs)
library(whisker)
library(withr)
library(viridisLite)
library(xfun)
library(yaml)
library(boot, lib.loc = "C:/Program Files/R/R-3.6.3/library")
library(class, lib.loc = "C:/Program Files/R/R-3.6.3/library")
library(cluster, lib.loc = "C:/Program Files/R/R-3.6.3/library")
library(compiler, lib.loc = "C:/Program Files/R/R-3.6.3/library")
install.packages("generics")
mod<-lm(y)
#scatter plot
plot(x,y)
cor (x,y)
mod<-lm(y~x)
summary(mod)
attributes(mod)
mod$coef
coef(mod)
plot(x,y, xlab="Homicide Case", ylab = "Murder Rate", col="coral2", main = "Regression")
abline(mod, col=1,lwd=1)
confint(mod)
#table data
reg<-matrix(c(17,3.4,194,38.8,48,9.6,3,0.6,238,47.6), ncol=2, byrow = TRUE)
rownames(reg) <-c("Asian/Pasific Islander","Black","Native American","Unknown","White")
colnames(reg) <-c("Homicide Case","Murder rate (2010-2014)")
reg=as.table(reg)
reg
x<-c(17,194,48,3,238)
y<-c(3.4,38.8,9.6,0.6,47.6)
#scatter plot
plot(x,y)
cor (x,y)
mod<-lm(y~x)
summary(mod)
attributes(mod)
mod$coef
coef(mod)
plot(x,y, xlab="Homicide Case", ylab = "Murder Rate", col="coral2", main = "Regression")
abline(mod, col=1,lwd=1)
confint(mod)
#table data
reg<-matrix(c(17,3.4,194,38.8,48,9.6,3,0.6,238,47.6), ncol=2, byrow = TRUE)
rownames(reg) <-c("Asian/Pasific Islander","Black","Native American","Unknown","White")
colnames(reg) <-c("Homicide Case","Murder rate (2010-2014)")
reg=as.table(reg)
reg
x<-c(17,194,48,3,238)
y<-c(3.4,38.8,9.6,0.6,47.6)
#scatter plot
plot(x,y)
cor (x,y)
mod<-lm(y~x)
summary(mod)
attributes(mod)
mod$coef
coef(mod)
plot(x,y, xlab="Homicide Case", ylab = "Murder Rate", col="coral2", main = "Regression")
abline(mod, col=1,lwd=1)
confint(mod)
#table data
reg<-matrix(c(78,22,77,23,65,35,79,21,66,34), ncol=2, byrow = TRUE)
rownames(reg) <-c("2010","2011","2012","2013","2014")
#table data
reg<-matrix(c(78,22,77,23,65,35,79,21,66,34), ncol=2, byrow = TRUE)
rownames(reg) <-c("2010","2011","2012","2013","2014")
colnames(reg) <-c("Male","Female")
reg=as.table(reg)
reg
x<-c(78,77,65,79,66)
y<-c(22,23,35,21,34)
#scatter plot
plot(x,y)
cor (x,y)
mod<-lm(y~x)
summary(mod)
attributes(mod)
mod$coef
coef(mod)
plot(x,y, xlab="Male", ylab = "Female", col="coral2", main = "Regression")
abline(mod, col=1,lwd=1)
confint(mod)
#table data
reg<-matrix(c(26,16,23,6,35,6,26,9,45,13,34,13,24,15,28,12,30,13,39,7,26,14,29,11), ncol=2, byrow = TRUE)
rownames(reg) <-c("Jnuary","February","March","April","May","June","July","September","October","November","December")
colnames(reg) <-c("Male","Female")
#table data
reg<-matrix(c(26,16,23,6,35,6,26,9,45,13,34,13,24,15,28,12,30,13,39,7,26,14,29,11), ncol=2, byrow = TRUE)
rownames(reg) <-c("Jnuary","February","March","April","May","June","July","September","October","November","December")
cor (x,y)
mod<-lm(y~x)
summary(mod)
attributes(mod)
mod$coef
coef(mod)
plot(x,y, xlab="Male", ylab = "Female", col="coral2", main = "Regression")
abline(mod, col=1,lwd=1)
confint(mod)
#table data
reg<-matrix(c(26,16,23,6,35,6,26,9,45,13,34,13,24,15,28,12,30,13,39,7,26,14,29,11), ncol=2, byrow = TRUE)
rownames(reg) <-c("January","February","March","April","May","June","July","September","October","November","December")
colnames(reg) <-c("Male","Female")
mod<-lm(x~y)
summary(mod)
attributes(mod)
mod$coef
coef(mod)
plot(x,y, xlab="Male", ylab = "Female", col="coral2", main = "Regression")
abline(mod, col=1,lwd=1)
#table data
reg<-matrix(c(23,4.6,477,95.4), ncol=2, byrow = TRUE)
rownames(reg) <-c("manslaughter by negligence","Murder or manslaughter")
colnames(reg) <-c("homicide victim","average per year")
reg=as.table(reg)
reg
x<-c(23,477)
y<-c(4.6,95.4)
#scatter plot
plot(x,y)
cor (x,y)
mod<-lm(y~x)
summary(mod)
attributes(mod)
library(readxl)
dataset_updated_data <- read_excel("~/SEMESTER II/PROBABILITY AND STATISTICS DATA ANALYSIS/ASSIGNMENT & PROJECT/PROJECT 2/Dataset and R Project/dataset updated data.xlsx")
View(dataset_updated_data)
library(readxl)
reg <- read_excel("~/SEMESTER II/PROBABILITY AND STATISTICS DATA ANALYSIS/ASSIGNMENT & PROJECT/PROJECT 2/Dataset and R Project/reg.xlsx")
View(reg)
confint(mod)
library(readxl)
reg <- read_excel("~/SEMESTER II/PROBABILITY AND STATISTICS DATA ANALYSIS/ASSIGNMENT & PROJECT/PROJECT 2/Dataset and R Project/reg.xlsx")
View(reg)
plot(reg$`Victim Sex`, reg$Year)
cor(reg$`Victim Sex`,reg$Year)
library(readxl)
reg <- read_excel("~/SEMESTER II/PROBABILITY AND STATISTICS DATA ANALYSIS/ASSIGNMENT & PROJECT/PROJECT 2/Dataset and R Project/reg.xlsx")
View(reg)
library(readxl)
reg <- read_excel("~/SEMESTER II/PROBABILITY AND STATISTICS DATA ANALYSIS/ASSIGNMENT & PROJECT/PROJECT 2/Dataset and R Project/reg.xlsx")
View(reg)
plot(reg$`Victim Race`, reg$`White Perpretrator`)
cor(reg$`Victim Race`, reg$`White Perpretrator`)
mod<- lm( reg$`White Perpretrator`~reg$`Victim Race`)
summary (mod)
attributes(mod)
mod$coef
coef(mod)
plot(reg$`Victim Race`,reg$`White Perpretrator`, xlab="Victim Race", ylab="White Perpretrator",
col="coral2", main="Regression")
abline(mod, col=1, lwd=1)
confint(mod)
library(readxl)
reg <- read_excel("~/SEMESTER II/PROBABILITY AND STATISTICS DATA ANALYSIS/ASSIGNMENT & PROJECT/PROJECT 2/Dataset and R Project/reg.xlsx")
View(reg)
plot(reg$`Victim Race`, reg$`White Perpretrator`)
cor(reg$`Victim Race`, reg$`White Perpretrator`)
mod<- lm( reg$`White Perpretrator`~reg$`Victim Race`)
summary (mod)
attributes(mod)
mod$coef
coef(mod)
plot(reg$`Victim Race`,reg$`White Perpretrator`, xlab="Victim Race", ylab="White Perpretrator",
col="coral2", main="Regression")
